Perseverers, recencies and deferrers : new experimental evidence for multiple inference strategies in understanding

In the course of understanding a text, a succession of decision points arise at which readers are faced with the task of choosing among alternative possible interpretations ofthattext. We present new experimental evidence that different readers use different inference strategies to guide their inference behavior during understanding. The choices available to an understander range from various alternative inferential paths to the option of making no inference at a particular point, leaving a 'loose end'. Different inference strategies result in observably different behaviors during understanding, including consistent differences in reading times, and different interpretations of a text. The preliminary experimental results given here so far consistently support a previously published set of hypotheses about the inference process that we have called Judgmental Inference theory

STRATEGIST : a program that models strategy-driven and content-driven inference behavior

In the course of understanding a text, different readers use different inference strategies to guide their choice of interpretations of the events in the text. This is in contrast to previous computer models of understanding, which all use the content-driven inference. The separate strategies are theorized to be composed of the same component inference processes, but of different rules for application of the processes. The use of different strategies occasionally results in different results of new experimental data and a working computer program, called STRATEGIST, that models both strategy-drive and content-driven inference behavior. The rules which make up two of these strategies are presented

A parallel-process model of on-line inference processing

This paper presents a new model of on-line inference processes during text understanding. The model, called ATLAST, integrates inference processing at the lexical, syntactic, and pragmatic levels of understanding, and is consistent with the results of controlled psychological experiments. ATLAST interprets input text through the interaction of independent but communicating inference processes running in parallel. The focus of this paper is on the initial computer implementation of the ATLAST model, and some observations and issues which arise from that implementation

Emotional inferences by pragmatics

It has for long been taken for granted that, along the course of reading a text, world knowledge is often required in order to establish coherent links between sentences (McKoon & Ratcliff 1992, Iza & Ezquerro 2000). The content grasped from a text turns out to be strongly dependent upon the reader’s additional knowledge that allows a coherent interpretation of the text as a whole. The world knowledge directing the inference may be of distinctive nature. Gygax et al. (2007) showed that mental models related to human action may be of a perceptual nature and may include behavioral as well as emotional elements. Gygax (2010), however, showed the unspecific nature of emotional inferences and the prevalence of behavioral elements in readers' mental models of emotions. Inferences are made in both directions; emotional inferences based on behavior and vice versa. Harris & de Rosnay (2002) and Pons et al. (2003) proved that different linguistic skills –in particular lexicon, syntax and semantics are closely related to emotion understanding. Iza & Konstenius (2010) showed that additional knowledge about social norms affects the participants’ prediction about would be inferred as the behavioral or emotional outcome of a given social situation. Syntactic and lexical abilities are the best predictors of emotion understanding, but making inferences is the only significant predictor of the most complex components (reflective dimension) of emotion comprehension in normal children. Recently, Farina et al. (2011) showed in a study that the relation between pragmatics and emotional inferences may not be so straight forward. Children with High Functioning Autism (HFA) and Asperger Syndrome (AS) present similar diagnostic profiles, characterized by satisfactory cognitive development, good phonological, syntactic and semantic competences, but poor pragmatic skills and socio-emotional competencies. After training in pragmatics a descriptive analyses showed the whole group to display a deficit in emotion comprehension, but high levels of pragmatic competences. This indicates a further need to study the relationship between emotion and inference in normal subjects too. We also suggest that while behavioral elements may indeed be of perceptual nature and the inference between emotion and behavior less culturally dependent especially when concerned with basic emotions -the inference concerned with social norms may be more complex and require elaborative inference. We suggest that in further studies a distinction between basic emotions and non basic emotions, social settings and non-social settings should be made. The cognitive models concerned with social action may be of more complex nature, but with recognizable features on lexical and syntactic levels.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Joint Video and Text Parsing for Understanding Events and Answering Queries

We propose a framework for parsing video and text jointly for understanding events and answering user queries. Our framework produces a parse graph that represents the compositional structures of spatial information (objects and scenes), temporal information (actions and events) and causal information (causalities between events and fluents) in the video and text. The knowledge representation of our framework is based on a spatial-temporal-causal And-Or graph (S/T/C-AOG), which jointly models possible hierarchical compositions of objects, scenes and events as well as their interactions and mutual contexts, and specifies the prior probabilistic distribution of the parse graphs. We present a probabilistic generative model for joint parsing that captures the relations between the input video/text, their corresponding parse graphs and the joint parse graph. Based on the probabilistic model, we propose a joint parsing system consisting of three modules: video parsing, text parsing and joint inference. Video parsing and text parsing produce two parse graphs from the input video and text respectively. The joint inference module produces a joint parse graph by performing matching, deduction and revision on the video and text parse graphs. The proposed framework has the following objectives: Firstly, we aim at deep semantic parsing of video and text that goes beyond the traditional bag-of-words approaches; Secondly, we perform parsing and reasoning across the spatial, temporal and causal dimensions based on the joint S/T/C-AOG representation; Thirdly, we show that deep joint parsing facilitates subsequent applications such as generating narrative text descriptions and answering queries in the forms of who, what, when, where and why. We empirically evaluated our system based on comparison against ground-truth as well as accuracy of query answering and obtained satisfactory results

Judgmental inference : a theory of inferential decision-making during understanding

In the course of understanding a text, a succession of decision points arise at which readers are faced with the task of choosing among alternative possible interpretations of what they're reading. Careful analysis of a wide range of sample texts reveals that such decisions are often based on complex evaluations of the interpretation being constructed, and sometimes cause the reader to construct and discard a number of intermediate inferences before settling on a final interpretation for a text.This paper introduces Judgmental Inference theory as a proposed scheme of evaluation metrics and mechanisms, derived from examination of inference decisions arising during text understanding. A series of programs, ARTHUR, MACARTHUR and JUDGE are described, which incorporate some of the metrics and mechanisms of Judgmental Inference, enabling them to understand texts more complex than those that can be handled by other understanding systems